Currently, the major challenge facing the complete genetic dissection of common multifactorial diseases is the identification of causal variants. The advent of robust technologies for high-throughput DNA sequencing provides an extremely powerful new tool for the identification of such causal variants. However, the development of equally robust strategies for the design and analysis of massively parallel DNA sequencing experiments for identification of causal variants is in its infancy. In this application, we propose to combine the proven phenotyping, clinical data management, and biostatistical expertise of our research team to address this important problem, by evaluating strategies that utilize emerging sequencing technologies to further our understanding of loci implicated in the pathology of psoriasis, a common autoimmune disorder. Our strategies will focus on the genetic loci previously implicated in disease susceptibility, including the MHC region. To this end, we propose the following specific aims: 1. Assemble DNA samples and detailed phenotypes from well-characterized, appropriately consented multiethnic samples for resequencing. 2. Interact with the sequencing center(s) regarding sequence data generation and particularly on analysis of the trace data to produce high quality genotype and haplotype data. 3. Carry out targeted resequencing and follow-up to identify the causative variants at least ten known non-MHC psoriasis loci. 4. Carry out long-read targeted resequencing of a 650 kb interval (HCG22-BAT5) known to carry at least 3 susceptibility loci for psoriasis and/or psoriatic arthritis. While we make specific proposals in each of these aims based on our own samples and other samples likely to be available, we understand that actual study plans will depend on the studies selected, the views of the U01 Steering Committee, and on technology development. We look forward to working together with colleagues from the other studies and believe our strengths in statistical design and analysis of genetic studies, our strong record of collaboration, and our unique sample sets, will allow us to be important contributors to such an effort. RELEVANCE: This work will build on recent genetic studies of psoriasis and other diseases by using large-scale DNA sequencing to identify small genetic differences between people with psoriasis compared to normal controls. This information will then be used to identify which of these differences actually contribute to causing psoriasis. Once we know which of the differences drive the disease process, they will become targets for the development of better treatments for psoriasis.